Conception d'un micro-systeme d'analyse d'images rapides en temps reel

SIGLEINIST T 71166 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

A nonlinear derivative

International audienceA nonlinear derivative is directly defined in the discrete domain. This derivative is motivated by the asymmetry of pattern in discrete signal as step or edge in 2D signal. Thanks to the special definition (in the discrete domain) of this derivative, pattern can be detected in a univocal way. This derivative is the only one able to perfectly detect and localize ideal edges in image. Beside this fundamental benefit, the derivative has the nice property to reduce noise. Ap- plications to edge detection, noise reduction and noise estimation are described and their performances are studied

Noise estimation from digital step-model signal

International audienceThis paper addresses the noise estimation in the digital domain and proposes a noise estimator based on the step signal model. It is efficient for any distribution of noise because it does not rely only on the smallest amplitudes in the signal or image. The proposed approach uses polarized/directional derivatives and a nonlinear combination of these derivatives to estimate the noise distribution (e.g., Gaussian, Poisson, speckle, etc.). The moments of this measured distribution can be computed and are also calculated theoretically on the basis of noise distribution models. The 1D performances are detailed, and as our work is mostly dedicated to image processing, a 2D extension is proposed. The 2D performances for several noise distributions and noise models are presented and are compared to selected other methods

Signal Restoration via a Splitting Approach

International audienceIn the present study, a novel signal restoration method from noisy data samples is presented and is termed as "signal split (SSplit)" approach. The new method utilizes Stein unbiased risk estimate estimator to split the signal, the Lipschitz exponents to identify noise elements and a heuristic approach for the signal reconstruction. However, unlike many noise removal techniques, the present method works only in the non-orthogonal domain. Signal restoration was performed on each individual part by finding the best compromise between the data samples and the smoothing criteria. Statistical results are quite promising and suggest better performance than the conventional shrinkage. Furthermore, the proposed method preserves the energy of the sharp peaks and edges which, is not however, the case for classical shrinkage methods

Non Linear Image Restoration in Spatial Domain

International audienceIn the present work, a novel image restoration method from noisy data samples is presented. The restoration was per-formed by using some heuristic approach utilizing data samples and smoothness criteria in spatial domain. Unlike most existing techniques, this approach does not require prior modelling of either the image or noise statistics. The proposed method works in an interactive mode to find the best compromise between the data (mean square error) and the smoothing criteria. The method has been compared with the shrinkage approach, Wiener filter and Non Local Means algorithm as well. Experimental results showed that the proposed method gives better signal to noise ratio as compared to the previously proposed denoising solutions. Furthermore, in addition to the white Gaussian noise, the effectiveness of the proposed technique has also been proved in the presence of multiplicative noise

Asymétrie des inflations relatives et "menus costs". Tests sur l'inflation française

The existence of menu costs at firm level must lead at macroeconomic level to a positive correlation between inflation and the skewness of the distribution of relative prices. For French data, this prediction turns true. The positive correlation which appears between inflation and skewness of the distribution of relative prices resists the introduction of variables which are important explanatory factors of inflation according to the results of the estimation of wage-price spirals on French data. We show, however, that in accordance with the results obtained for American data, this positive correlation can also be obtained in a model without menu costs, when one takes into account the fact that the tail of the price distribution is generally fatter than the normal one.Asymmetry in relative-price inflation and menu costs: tests on french data The existence of menu costs at firm level must lead at macroeconomic level to a positive correlation between inflation and the skewness of the distribution of relative prices. For French data, this prediction turns true. The positive correlation which appears between inflation and skewness of the distribution of relative prices resists the introduction of variables which are important explanatory factors of inflation according to the results of the estimation of wage-price spirals on French data. We show, however, that in accordance with the results obtained for American data, this positive correlation can also be obtained in a model without menu costs, when one takes into account the fact that the tail of the price distribution is generally fatter than the normal one.Bonnet Xavier, Dubois Eric, Fauvet Laurent. Asymétrie des inflations relatives et "menus costs". Tests sur l'inflation française. In: Revue économique, volume 50, n°3, 1999. pp. 547-556

EDA, approche non linéaire de débruitage des signaux cardiaques

National audienc

The noise estimator NOLSE

This report is not self-content and presents complementary definitions and demonstrations for the paper "Noise estimation from digital step-model signal" published inTransactions on Image Processing

Edge-Preserving Image Denoising Based on Lipschitz Estimation

International audienceThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC B

Local surface curvature analysis based on reflection estimation

International audienc